/**
 * Copyright 2023 Huawei Technologies Co., Ltd
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "kernel/ascend/acl_ir/acl_adapter_info.h"
#include "include/backend/common/kernel_graph/anf_runtime_algorithm.h"

namespace mindspore::device::ascend {
namespace {
constexpr size_t kReduceSumInputSize = 4;
}

bool IsNeedSkipExecute(const std::vector<KernelTensor *> &inputs) {
  if (inputs.size() != kReduceSumInputSize) {
    MS_LOG(EXCEPTION) << "For Reducesum input size must be 4, but got " << inputs.size();
  }
  auto is_real_skip =
    AnfAlgo::IsDynamicShapeSkipExecute(inputs[kIndex3]->GetValueWithCheck<bool>(), inputs[kIndex1]->GetShapeVector());
  return is_real_skip;
}

REGISTER_ACL_OP(ReduceSum).InputCheckSelector(&IsNeedSkipExecute);
}  // namespace  mindspore::device::ascend
